Open AccessValidation of the Mobile App–Recorded Circadian Rhythm by a Digital Footprint
Author(s) -
YuHsuan Lin,
Bo-Yu Wong,
YuanChien Pan,
YuChuan Chiu,
Yang-Han Lee
Publication year - 2019
Publication title -
jmir mhealth and uhealth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.356
H-Index - 50
ISSN - 2291-5222
DOI - 10.2196/13421
Subject(s) - circadian rhythm , rhythm , sleep (system call) , mobile apps , psychology , smartphone app , audiology , actigraphy , medicine , computer science , neuroscience , world wide web , operating system
Background Modern smartphone use is pervasive and could be an accessible method of evaluating the circadian rhythm and social jet lag via a mobile app. Objective This study aimed to validate the app-recorded sleep time with daily self-reports by examining the consistency of total sleep time (TST), as well as the timing of sleep onset and wake time, and to validate the app-recorded circadian rhythm with the corresponding 30-day self-reported midpoint of sleep and the consistency of social jetlag. Methods The mobile app, Rhythm, recorded parameters and these parameters were hypothesized to be used to infer a relative long-term pattern of the circadian rhythm. In total, 28 volunteers downloaded the app, and 30 days of automatically recorded data along with self-reported sleep measures were collected. Results No significant difference was noted between app-recorded and self-reported midpoint of sleep time and between app-recorded and self-reported social jetlag. The overall correlation coefficient of app-recorded and self-reported midpoint of sleep time was .87. Conclusions The circadian rhythm for 1 month, daily TST, and timing of sleep onset could be automatically calculated by the app and algorithm.